def test_rand_mps_right_canonize(self):
n = 10
k = MPS_rand_state(n,
10,
site_tag_id="foo{}",
tags='bar',
normalize=False)
k.right_canonize(normalize=True)
assert_allclose(k.H @ k, 1)
p_tn = (k.H & k) ^ slice(..., 0, -1)
assert_allclose(p_tn['foo1'].data, np.eye(10), atol=1e-13)
def test_rand_mps_right_canonize_with_bra(self):
n = 10
k = MPS_rand_state(n,
10,
site_tag_id="foo{}",
tags='bar',
normalize=False)
b = k.H
k.right_canonize(normalize=True, bra=b)
assert_allclose(b @ k, 1)
p_tn = (b & k) ^ slice(..., 0)
assert_allclose(p_tn['foo1'].data, np.eye(10), atol=1e-13)
def test_schmidt_values_entropy_gap_simple(self):
n = 12
p = MPS_rand_state(n, 16)
p.right_canonize()
svns = []
sgs = []
for i in range(1, n):
sgs.append(p.schmidt_gap(i, current_orthog_centre=i - 1))
svns.append(p.entropy(i, current_orthog_centre=i))
pd = p.to_dense()
ex_svns = [entropy_subsys(pd, [2] * n, range(i)) for i in range(1, n)]
ex_sgs = [schmidt_gap(pd, [2] * n, range(i)) for i in range(1, n)]
assert_allclose(ex_svns, svns)
assert_allclose(ex_sgs, sgs)